Upload SSL4EO-L-Benchmark.py with huggingface_hub

SSL4EO-L-Benchmark.py

@@ -7,7 +7,13 @@ import tifffile
 import pandas as pd
 import numpy as np
 
-from GFMBench.datasets.base_dataset import GFMBenchDataset
+from torchgeo.datasets.cdl import CDL
+from torchgeo.datasets.nlcd import NLCD
+
+CMAPS = {
+    'nlcd': NLCD.cmap,
+    'cdl': CDL.cmap,
+}
 
 S2_MEAN = [752.40087073, 884.29673756, 1144.16202635, 1297.47289228, 1624.90992062, 2194.6423161, 2422.21248945, 2581.64687018, 2368.51236873, 1805.06846033]
 
@@ -71,6 +77,13 @@ class SSL4EOLBenchmarkDataset(datasets.GeneratorBasedBuilder):
         self.NUM_CHANNELS = num_channels[name] if name else num_channels['etm_sr_cdl']
         self.metadata = metadata[name] if name else metadata['etm_sr_cdl']
 
+        product = name.split('_')[-1]
+        cmap = CMAPS[product]
+        classes = list(cmap.keys())
+        ordinal_map = np.zeros(max(cmap.keys()) + 1, dtype=np.int64)
+        for v, k in enumerate(classes):
+            ordinal_map[k] = v
+
         super().__init__(*args, **kwargs)
 
     def _info(self):
@@ -86,7 +99,7 @@ class SSL4EOLBenchmarkDataset(datasets.GeneratorBasedBuilder):
                 "spatial_resolution": datasets.Value("int32"),
             }),
         )
-    
+
     def _split_generators(self, dl_manager):
         if isinstance(self.DATA_URL, list):
             downloaded_files = dl_manager.download(self.DATA_URL)
@@ -137,6 +150,7 @@ class SSL4EOLBenchmarkDataset(datasets.GeneratorBasedBuilder):
 
             label_path = os.path.join(data_dir, row.label_path)
             label = self._read_image(label_path).astype(np.int32)
+            label = self.ordinal_map[label]
 
             sample = {
                 "optical": optical,